Python ReadData.read_all_val示例

示例#1

        model = ConvLSTMModel2(hidden_states,
                               classes,
                               attention_size=attention_size,
                               use_attention=args.use_attention)
    else:
        model = ConvModel(classes)

reader = ReadData(args.training_csv,
                  args.embedding,
                  args.classes,
                  batch_size=args.batch_size,
                  no_samples=args.no_samples,
                  train_val_split=args.train_val_split)

print('Reading Validation data.')
val_x, val_y = reader.read_all_val()
if args.model.startswith('cnn'):
    val_x = np.reshape(val_x, (val_x.shape[0], timesteps, embed_size, 1))

with tf.name_scope('Model'):
    prediction = model.model(x)

with tf.name_scope('Loss'):
    crossent = tf.nn.softmax_cross_entropy_with_logits_v2(logits=prediction,
                                                          labels=y)
    cost_func = (tf.reduce_mean(crossent)) / args.batch_size
    #cost_func = tf.reduce_mean(crossent)

lr = tf.placeholder('float', [])
learning_rate = args.learning_rate